Positioning Multi-Intelligence Agents for Healthcare Enterprises: Toward Evolving Cyber-Physical-Social SystemsSource: Journal of Computing and Information Science in Engineering:;2025:;volume( 025 ):;issue:012Author:Milisavljevic-Syed, Jelena
DOI: 10.1115/1.4070442Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Abstract. Healthcare enterprises, including providers, payers, pharmaceutical and biotech firms, medical device manufacturers, health IT companies, regulators, supply chain actors, and hybrid care models, face the complex challenge of balancing economic viability with equitable and environmentally-responsible care delivery. This challenge is compounded by entrenched asymmetries in access to information, analytical capabilities, and control over resources and decision-making, which constrain responsiveness and obstruct transitions toward inclusive, adaptive service delivery. In this article, the author argues for designing healthcare systems for punctuated evolution, rapid, transformative adjustments to shifting patient needs, emerging technologies, and evolving regulatory or environmental conditions, while operating in a poised equilibrium that balances stability and exploration. A smart service perspective is advanced, prioritizing adaptability, stakeholder alignment, and long-term resilience across healthcare and related domains. The author presents a computational and conceptual framework positioning smart services as evolving cyber-physical-social systems (eCPSS), anchored in the novel construct of multi-intelligence agents (MIAs). The core contribution is a mental model integrating physical, cyber, and social domains to address persistent asymmetries in intelligence, information, and resources. This model operationalizes adaptive intelligence by enabling MIAs to perceive context, learn from interaction, and align behavior with dynamic service goals. It introduces evolvability, the maintained capacity of an eCPSS to generate and retain beneficial variations while remaining viable. The healthcare sector is used to illustrate the framework's relevance, with a discussion of its extensibility to other smart service domains.
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| contributor author | Milisavljevic-Syed, Jelena | |
| date accessioned | 2026-08-23T07:53:03Z | |
| date available | 2026-08-23T07:53:03Z | |
| date copyright | 2025/12/01 | |
| date issued | 2025 | |
| identifier issn | 1530-9827 | |
| identifier other | jcise-25-1401.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4315756 | |
| description abstract | Abstract. Healthcare enterprises, including providers, payers, pharmaceutical and biotech firms, medical device manufacturers, health IT companies, regulators, supply chain actors, and hybrid care models, face the complex challenge of balancing economic viability with equitable and environmentally-responsible care delivery. This challenge is compounded by entrenched asymmetries in access to information, analytical capabilities, and control over resources and decision-making, which constrain responsiveness and obstruct transitions toward inclusive, adaptive service delivery. In this article, the author argues for designing healthcare systems for punctuated evolution, rapid, transformative adjustments to shifting patient needs, emerging technologies, and evolving regulatory or environmental conditions, while operating in a poised equilibrium that balances stability and exploration. A smart service perspective is advanced, prioritizing adaptability, stakeholder alignment, and long-term resilience across healthcare and related domains. The author presents a computational and conceptual framework positioning smart services as evolving cyber-physical-social systems (eCPSS), anchored in the novel construct of multi-intelligence agents (MIAs). The core contribution is a mental model integrating physical, cyber, and social domains to address persistent asymmetries in intelligence, information, and resources. This model operationalizes adaptive intelligence by enabling MIAs to perceive context, learn from interaction, and align behavior with dynamic service goals. It introduces evolvability, the maintained capacity of an eCPSS to generate and retain beneficial variations while remaining viable. The healthcare sector is used to illustrate the framework's relevance, with a discussion of its extensibility to other smart service domains. | |
| publisher | The American Society of Mechanical Engineers (ASME) | |
| title | Positioning Multi-Intelligence Agents for Healthcare Enterprises: Toward Evolving Cyber-Physical-Social Systems | |
| type | Journal Paper | |
| journal volume | 25 | |
| journal issue | 12 | |
| journal title | Journal of Computing and Information Science in Engineering | |
| identifier doi | 10.1115/1.4070442 | |
| tree | Journal of Computing and Information Science in Engineering:;2025:;volume( 025 ):;issue:012 | |
| contenttype | Fulltext |